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Multigroup Multimodality Index: A Method to Solve the Issue of Transport Mode Classification in Measuring Multimodality

Authors :
Xingxing Fu
Dea van Lierop
Dick Ettema
Source :
Findings.
Publication Year :
2023
Publisher :
Network Design Lab - Transport Findings, 2023.

Abstract

Recent methods to measure multimodality only consider the diversity and evenness of mode use, while ignoring that the classification of transport modes also matters. This study proposes a multigroup multimodality index to measure the extent of being multimodal at both single mode and mode group levels in a nested manner. The index is compared with the two most commonly used indices, the Herfindahl-Hirschman index and the Shannon Entropy index, to assess its reliability and improvement over existing approaches. Results show that the multigroup multimodality index can simultaneously distinguish the degree of being multimodal at both mode level and group level, which addresses the classification issue in measuring multimodality.

Subjects

Subjects :
General Engineering

Details

ISSN :
26528800
Database :
OpenAIRE
Journal :
Findings
Accession number :
edsair.doi...........49b72ae49ffbaaf2d9448464b01de529
Full Text :
https://doi.org/10.32866/001c.72072